Wednesday, 01 July 2026 10:30 AM
Environmental, Social and Governance
NORTHAMPTON, MA / ACCESS Newswire / July 1, 2026 / Originally published on GoDaddy Resource Library
What does "Your Work. Global Impact." mean to you personally?
When I joined Care Engineering in the last quarter of 2024, the India presence was small - a lean team in Gurgaon and the Pune center in a nascent phase. With around 25 years of industry experience, specifically in building engineering teams from under 50 employees to a few thousand who are passionate about engineering discipline, I had a mammoth task of building those proud units as well as accelerating the AI challenge at hand. Standing up those teams, building Guide Assist v2, and simultaneously contributing to the migration of a global contact center and the rebuild of an AI platform gave us a very direct answer to what this phrase means. The work my team does in Gurgaon and Pune lands directly in front of GoDaddy customers and Guides across the world - every single day.
The moment it really hit me was when the AI framework components we built started showing measurable positive outcomes for Guides handling customer conversations globally. These weren't built by an existing team alone - they were built together, from the ground up, by engineers in both the US and India who owned them end to end. "Global impact" stopped being a tagline and became a standard we held ourselves to.
For me personally & with the fast paced AI world, it means innovation with responsibility. When you know your system is running in a live conversation, innovation & reliability aren't optional - they're part of the job.
How do teams balance innovation with reliability?
Honestly? The hardest way possible - by doing both at the same time, not sequentially.
Running a live contact center while simultaneously migrating infrastructure and building AI capabilities that couldn't wait taught me this directly. The teams that came through that period without breaking everything else were the ones with disciplined release practices already in place.
That experience shaped how I think about this now. Innovation gets to move fast because we don't compromise on the foundation. We introduced release trains specifically to make delivery deterministic - you can move boldly when you know the guardrails are real, not just documented somewhere. We invested in AI observability not to slow things down but so we could see exactly what was happening inside our agents in production and iterate quickly with confidence.
The short version: reliability is what earns you the right to innovate. Without it, you're not moving fast - you're just accumulating risk you'll pay for later.
What leadership learning moment shaped you most?
Some experiences, like visiting the teleperformance center in Mohali multiple times during our contact center migration was one of those experiences that quietly shapes how you think.
You can architect systems from a distance - read the metrics, review the logs, sit in the design reviews. But walking the floor of a live care center, watching the customer pain points, watching Guides handle back-to-back customer conversations, understanding the micro-frustrations in their tools, the cognitive load of switching contexts mid-call - that changes how you build. You stop optimizing for what looks good in a demo and start optimizing for what actually helps a human being do their job better under pressure.
That experience directly shaped how we approached the AI framework and the components that needed to be a part of the CARE foundation - these weren't designed in the abstract. They were designed with the CARE's future needs & specific personas in mind: a guide trying to resolve a customer's problem quickly and confidently, the customer itself getting a great experience, both with and without a guide.
The leadership lesson: get close to the problem before you get close to the solution. The best engineering decisions I've made at GoDaddy trace back to something I saw or heard on that floor.
What excites you most about GoDaddy's AI future?
The shift from building AI features to building the platform that makes AI-powered CARE possible & effective.
This shift is also the moment Care Engineering stops being seen as a delivery team and starts being seen as the very foundation of GoDaddy's customer experience.
Right now, what we've built in Care Engineering - the capabilities, the framework and the features on top - is starting to look less like a set of projects and more like a platform & the foundation of how customer experience will look like from here. That transition is exciting because it changes what becomes possible for teams across GoDaddy.
We ran the AI Boulder program specifically to seed AI champions inside India engineering teams - people who can carry the capability forward, not just consume tools built elsewhere. Seeing those individuals emerge and start pulling their teams forward is genuinely one of the most exciting things I've been part of.
What's ahead is "agentic systems" that don't just assist guides but handle entire workflows, for customers as well as guides, for all channels, be it messaging or voice - personalized, context-aware, and operating at GoDaddy scale. We've been building the components that make that possible. The most exciting part is that much of that foundation was built in the US and India together, by teams that didn't exist in this form a year ago.
What are the non-negotiables in how your team's work?
Three things, and I hold these firmly.
Ownership, not handoffs. A team that builds something owns it - in production and under pressure. We don't build things and throw them over walls. This was especially important as we were establishing new teams or scaling up existing ones in India; I wanted the culture of full ownership to be there from day one, not retrofitted later.
Deterministic delivery. We introduced release trains because unpredictable delivery is expensive - for the teams, for stakeholders, and for our customers. Predictability isn't about slowing down; it's about building trust that lets you move faster over time. If a team can't say when something will ship and actually mean it, that's the first thing we fix.
Honest engineering conversations. I expect my teams to tell me when something won't work - technically, timeline-wise, or in terms of what a product can actually deliver. The cost of a hard conversation early is always lower than the cost of avoiding it. I'd rather have an engineer who pushes back with evidence than one who ships something they knew was wrong.
A note of gratitude
None of this journey has been a solo act. I'm deeply grateful to my peers across the US and India who aligned with us, challenged us, and trusted us with consequential work from the very beginning. To my managers who backed the direction even when the path wasn't fully clear - thank you. And to every engineer in Gurgaon and Pune who showed up, upskilled rapidly, backed each other under pressure, and delivered at a pace this fast-moving AI environment demanded - this story is yours as much as mine.
What I'm most proud of isn't any single delivery. It's that when things got hard, this team held together and performed as one cohesive unit.
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SOURCE: GoDaddy